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Machine-learning Techniques in Economics. New Tools for Predicting Economic Growth

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dc.contributor.authorAtin Basuchoudhary, James T. Bang, Tinni Senspa
dc.date.accessioned2023-02-21T19:35:46Z
dc.date.available2023-02-21T19:35:46Z
dc.description91 p. , Figuresspa
dc.description.otherAGNB November 2022spa
dc.description.tableofcontentsIn this book, we develop a Machine Learning framework to predict economic growth and the likelihood of recessions. In such a framework, different algorithms are trained to identify an internally validated ser of correlates of a particular target within a training sample. These algorithms are then validated in a test sample. Why does this matter for predicting growth and business cycles, or for predicting other economic phenomena? In the rest of this chapter, we discuss how Machine Learning methodologies are useful to economics in general and to predicting growth and recessions in particular. In fact, the social sciences are increasingly using these techniques for precisely the reasons we outline. While Machine Learning itserf is no a new idea, advances in computing technology combined with a recognition of its applicabolity to economic questions make it a new tool for economists (Varian 2014).Machine Learning techniques present easily interpretable results particularly helpful to policy makers in ways not possible with the standard sophisticated econometric techniques. Moreover, these methodologies come with powerful validation criteria that give both researchers and policy makers a nuanced sense of confidence in understanding economic phenomenon.spa
dc.identifier.bitstream10433.pdfspa
dc.identifier.collection1- GENERALspa
dc.identifier.isbn978-3-319-69013-1spa
dc.identifier.local10433spa
dc.identifier.mfn6308spa
dc.identifier.signatureCG10433spa
dc.identifier.urihttps://hdl.handle.net/20.500.14000/1127
dc.language.localengspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa
dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)spa
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.subjectWhy this book?spa
dc.subjectData, Variables, and Their Sourcesspa
dc.subjectMethodologyspa
dc.subjectPredicting a Country - s Growth: A First Lookspa
dc.subjectPredicting Economic Growth: Which Variables Matter.spa
dc.subjectPredicting Recessions: What We Learn from Widening the Goalpostsspa
dc.titleMachine-learning Techniques in Economics. New Tools for Predicting Economic Growthspa
dc.typeLibrospa
dc.type.coarhttp://purl.org/coar/resource_type/c_2f33spa
dc.type.coarversionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/bookspa
dc.type.localColección Generalspa
dc.type.redcolhttp://purl.org/redcol/resource_type/LIBspa
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa
dspace.entity.typePublication
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